Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 10th International Symposium on Open Collaboration, OpenSym 2014 |
| Pages | F1 |
| ISBN (electronic) | 9781450330169 |
| Publication status | Published - 2014 |
| Event | 10th International Symposium on Open Collaboration, OpenSym 2014 - Berlin, Germany Duration: 27 Aug 2014 → 29 Aug 2014 |
Publication series
| Name | Proceedings of the 10th International Symposium on Open Collaboration, OpenSym 2014 |
|---|
Abstract
The Web of data is constantly evolving based on the dynamics of its content. Current Web search engine technologies consider static collections and do not factor in explicitly or implicitly available temporal information, that can be lever- aged to gain insights into the dynamics of the data. In this paper, we hypothesize that by employing the temporal as- pect as the primary means for capturing the evolution of entities, it is possible to provide entity-based accessibility to Web archives. We empirically show that the edit activity on Wikipedia can be exploited to provide evidence of the evolution of Wikipedia pages over time, both in terms of their content and in terms of their temporally defined relation- ships, classified in literature as events. Finally, we present results from our extensive analysis of a dataset consisting of 31; 998 Wikipedia pages describing politicians, and ob- servations from in-depth case studies. Our findings reect the usefulness of leveraging temporal information in order to study the evolution of entities and breed promising grounds for further research.
Keywords
- Entity Evolution, Events, Temporal Information, Wikipedia
ASJC Scopus subject areas
- Computer Science(all)
- Software
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Proceedings of the 10th International Symposium on Open Collaboration, OpenSym 2014. 2014. p. F1 (Proceedings of the 10th International Symposium on Open Collaboration, OpenSym 2014).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Information evolution in wikipedia
AU - Ceroni, Andrea
AU - Georgescu, Mihai
AU - Gadiraju, Ujwal
AU - Naini, Kaweh Djafari
AU - Fisichella, Marco
PY - 2014
Y1 - 2014
N2 - The Web of data is constantly evolving based on the dynamics of its content. Current Web search engine technologies consider static collections and do not factor in explicitly or implicitly available temporal information, that can be lever- aged to gain insights into the dynamics of the data. In this paper, we hypothesize that by employing the temporal as- pect as the primary means for capturing the evolution of entities, it is possible to provide entity-based accessibility to Web archives. We empirically show that the edit activity on Wikipedia can be exploited to provide evidence of the evolution of Wikipedia pages over time, both in terms of their content and in terms of their temporally defined relation- ships, classified in literature as events. Finally, we present results from our extensive analysis of a dataset consisting of 31; 998 Wikipedia pages describing politicians, and ob- servations from in-depth case studies. Our findings reect the usefulness of leveraging temporal information in order to study the evolution of entities and breed promising grounds for further research.
AB - The Web of data is constantly evolving based on the dynamics of its content. Current Web search engine technologies consider static collections and do not factor in explicitly or implicitly available temporal information, that can be lever- aged to gain insights into the dynamics of the data. In this paper, we hypothesize that by employing the temporal as- pect as the primary means for capturing the evolution of entities, it is possible to provide entity-based accessibility to Web archives. We empirically show that the edit activity on Wikipedia can be exploited to provide evidence of the evolution of Wikipedia pages over time, both in terms of their content and in terms of their temporally defined relation- ships, classified in literature as events. Finally, we present results from our extensive analysis of a dataset consisting of 31; 998 Wikipedia pages describing politicians, and ob- servations from in-depth case studies. Our findings reect the usefulness of leveraging temporal information in order to study the evolution of entities and breed promising grounds for further research.
KW - Entity Evolution
KW - Events
KW - Temporal Information
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84908611912&partnerID=8YFLogxK
U2 - 10.1145/2641580.2641612
DO - 10.1145/2641580.2641612
M3 - Conference contribution
AN - SCOPUS:84908611912
T3 - Proceedings of the 10th International Symposium on Open Collaboration, OpenSym 2014
SP - F1
BT - Proceedings of the 10th International Symposium on Open Collaboration, OpenSym 2014
T2 - 10th International Symposium on Open Collaboration, OpenSym 2014
Y2 - 27 August 2014 through 29 August 2014
ER -